Many companies are developing autonomous vehicles for commercial and personal use on existing roadways for a variety of applications, including but not limited to personal taxi services, delivery services, and the like. In accordance with the present invention, an autonomous vehicle is a vehicle capable of operating without a human driver. Such vehicles can be designed to operate utilizing an onboard computer and a system of sensors designed to drive, steer, and otherwise operate the vehicle in the same manner as if there were a human operator. It is envisioned that fleets of autonomous vehicles will soon be available, similar to a network of taxis, buses or delivery vans, whereby a user can request an autonomous vehicle to pick-up, transport and drop off passengers, or pick-up, transport, and deliver packages or the like, on demand. Alternatively, users can own an autonomous vehicle for personal use and use it for ordinary tasks, such as commuting to work, running errands, dropping the kids off at school, for travel, or the like.
Current autonomous vehicles in the development and testing stages generally utilize multiple systems to fully operate the vehicle without a human operator. First, a standard GPS system is used to plan a route for the vehicle. Taking into account the starting point and the destination for a trip, as well as other factors such as traffic conditions, road closures, weather conditions, preferred routes, toll roads, etc., the GPS system determines the best route for the vehicle to take. However, for safe and efficient operation, autonomous vehicles also need a system to recognize dynamic conditions along the route during operation of the vehicle. Such a system may be referred to as an augmented GPS system, which utilizes an array of technologies, such as cameras, sensors, radar, LIDAR and lasers to provide a three-dimensional view around the vehicle during operation. Such a system can keep track of other cars around the vehicle; detect obstacles or hazards around the car, in the road up ahead, or approaching the car from the front, rear, or sides; and determine the location of the edge of the road or travel lane, upcoming turns, hills or descents, and assess general road conditions ahead, behind and around the vehicle. Autonomous vehicles also require a centralized system within the car to process the information provided from the GPS system and augmented GPS system and utilize the processed information to operate the vehicle. Such commonly utilized systems generally include a Computer Area Network (CAN) bus in the vehicle to communicate with and coordinate operation of the GPS system, augmented GPS system and other autonomous vehicle operating systems.
Non-autonomous vehicles also utilize similar technology to back-up a human driver. For example, cars have used various forms of cruise control for decades. More recently, cars have been equipped with systems that will autonomously parallel park the car. Many modern cars are now equipped with systems that assist the driver when the car begins to drift out of its lane on the highway, or brake the car if it is getting too close to the car in front of it, or alert the driver if there is an object in the road ahead.
Until guidance systems on-board autonomous vehicles match or exceed the perception and analytical decision-making ability of human drivers, there will be numerous ongoing daily situations which will frustrate the ability of a full autonomous vehicle to properly and dynamically respond to, or react to, its surroundings. Moreover, until autonomous vehicles can safely rely upon existing operational systems and sensors for safe and efficient operation and eliminate essentially all risks, the public will continue to be hesitant to put full faith in true autonomous operation of such vehicles. Indeed, numerous “real-world” autonomous vehicular tests have resulted in guidance failures, accidents, etc., caused by guidance systems and sensors that have failed to adequately detect, recognize and/or react in a timely fashion due to challenging ambient conditions, and as a result, most autonomous vehicle testing is usually limited to warm, sunny climate areas.
While various optically-based automotive and/or autonomous guidance systems and sensors (e.g., video, LIDAR, etc.) are capable of performing well under ideal visual and ambient conditions, their capabilities can quickly diminish to unusable levels under adverse ambient conditions, such as during or shortly after rain, snowfall, fog, etc., or when it is dark outside and in low-lighted areas of the roadway. Additionally, while the existing level of “on-board” sensors, cameras, devices, and interfaces can alter an autonomous vehicle's driving characteristics to a limited degree (e.g., by braking for unexpected obstacles and/or other vehicles, or steering a vehicle if it drifts out of its lane, or adjusting the propulsion of the vehicle, etc.), there is currently an inherent extreme deficiency in giving autonomous vehicles the ability to react properly to harsh ambient conditions, such as fog, snow, heavy winds or extreme darkness, that can confuse or render useless many optically dependent sensors. Existing GPS navigation systems alone, and high-resolution digital maps cannot be absolutely relied upon, as their databases do not cover the majority of roadways, and are constantly becoming outdated. Accordingly, there is a need to improve upon existing optically-based guidance systems and sensors to ensure that operation of an autonomous vehicle is safe and efficient in all conditions.
Accordingly, there is a need for an improved system for the operation of autonomous vehicles, as well as manually driven vehicles, to continue to properly guide themselves during conditions on a roadway that overcomes the drawbacks and limitations of existing dynamic guidance systems. Further, there is a need for a system that utilizes infra-red detection and imaging with sensors that can assist in the safe and efficient operation of vehicles in response to unexpected and unpredicted situations or conditions on a roadway, and that will aid the vehicles in determining appropriate responsive actions in a quick and expeditious manner.